In order to support higher data rates in mobile telecommunications networks, the third generation partnership project (3GPP) introduced a new air interface based on orthogonal frequency domain multiple access (OFDMA) techniques as the long term evolution (LTE) of the UMTS network. LTE supports a peak downlink data rate of 300 Mbps and a peak uplink data rate of 75 Mbps.
Since 2009 3GPP has worked on the further improvement of LTE to meet the requirements of a more demanding standard known as LTE Advanced (LTE-A). LTE and LTE-A use adaptive modulation and coding to achieve optimum throughput in different channel conditions, by modifying, at the transmitter, the coding rate and modulation order according to the current quality of the propagation channel between the transmitter and a user equipment (UE) such as a mobile telephone receiving the transmitted signal. This adaptive modulation and coding requires accurate estimation of signal to noise power ratio (SNR) by the UE, which can have a significant effect on system throughput.
It is known to use a moving average filter to filter out noise from a signal received by a UE. Comparing the input and output of the moving average filter provides an estimate of the noise power in the received signal. Estimating the noise power in a received signal using a moving average filter in this way gives good results in additive white Gaussian noise (AWGN) propagation channels. However, in time varying channels, the accuracy of noise power estimation using this technique is limited.
A number of other noise estimation algorithms are known, but these are impractical for an LTE receiver, as either they cannot meet the performance requirements for multipath fading channels with large propagation delays or mobility, or they are not compliant with the 3GPP standard, or the algorithms are too complex for implementation in a practical receiver.